It’s a generally accepted maxim that the business community’s fascination with big data, which started in the mid-2000s, ran out of steam about five years ago. But that’s only partly true. While the ...

Last week’s Informatica World 2016 brought out a lot of talk involving data quality, real-time live data and the automation of ingesting and analyzing data in order to turn it into something ...

Having data scientists collaborate with devops and engineers leads to better business outcomes, but understanding their different requirements is key Data scientists have some practices and needs in ...

It may be a stretch to call data science commonplace, but the question “what’s next” is often heard with regard to analytics. And then the conversation often turns straight to Artificial Intelligence ...

Overcoming DevOps obstacles—such as slow, manual, poor-quality test data—is key toward accelerating pipelines. With speed being a central success factor for DevOps pipelines, increasing velocity ...

As system architecture moves to the cloud, understanding the impacts of new code releases and points of failure requires a whole new approach. The increase in agility, bandwidth, and security has been ...

It’s sad but true, most attempts by companies to leverage data as a strategic asset fail. The challenge of both managing vast amounts of disparate data and then distributing it to those who can use it ...

Over the past decade, the push for digital transformation has touched nearly every industry and has changed the game for BI. Now, every system and device has a digital trail, with data varying in ...

There has been overwhelming momentum to the practice of DevOps in recent years, and for good reason. Organizations are under tremendous pressure to get software up and running -- or out the door if ...

Data governance is an umbrella term encompassing several different disciplines and practices, and the priorities often depend on who is driving the effort. Chief data officers, privacy officers, ...